195 件 ・ 関連度順
概要と使いどころ
You are an expert in Bolt.new by StackBlitz, the AI-powered full-stack development environment that runs entirely in the browser. You help developers go from idea to deployed app in minutes using natural language prompts — Bolt generates complete applications with frontend, backend, database, and deployment, all running in a WebContainer without local setup.
日本語の概要は準備中です。原文の説明を表示しています。
Firebase gives you a complete backend in minutes - auth, database, storage, functions, hosting. But the ease of setup hides real complexity. Security rules are your last line of defense, and they're often wrong. Firestore queries are limited, and you learn this after you've designed your data model. This skill covers Firebase Authentication, Firestore, Realtime Database, Cloud Functions, Cloud Storage, and Firebase Hosting. Key insight: Firebase is optimized for read-heavy, denormalized data. If you're thinking relationally, you're thinking wrong. 2025 lesson: Firestore pricing can surprise you. Reads are cheap until they're not. A poorly designed listener can cost more than a dedicated database. Plan your data model for your query patterns, not your data relationships. Use when "firebase, firestore, firebase auth, cloud functions, firebase storage, realtime database, firebase hosting, firebase emulator, security rules, firebase admin, firebase, firestore, cloud-functions, serverless, backend, realtime, authentication, google-cloud" mentioned.
日本語の概要は準備中です。原文の説明を表示しています。
The new frontier of audio: AI-generated music with Suno and Udio, AI sound effects with ElevenLabs, AI voice cloning, and AI audio enhancement. This skill covers the full spectrum of neural audio synthesis and manipulation. We're in an era where a single person can produce broadcast-quality audio content that would have required studios, musicians, and engineers. AI doesn't replace musical talent—it democratizes production capability. Original compositions in minutes. Custom sound design in seconds. Voice in any language instantly. The practitioners of this skill understand both the creative potential and the ethical considerations. They know when AI audio enhances creativity and when it needs human touch. They're audio directors who orchestrate AI tools like instruments in a symphony. Use when "AI music, generate music, Suno, Udio, AI audio, AI sound, generate soundtrack, background music, sound effects, audio generation, jingle, AI score, stem separation, ai-audio, music, suno, udio, sound-effects, soundtrack, generation, audio-branding, production" mentioned.
日本語の概要は準備中です。原文の説明を表示しています。
Check for Faster-Whisper (preferred - 4-5x faster) workflow skill. Use this skill when the user needs Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
日本語の概要は準備中です。原文の説明を表示しています。
Check for Faster-Whisper (preferred - 4-5x faster) workflow skill. Use this skill when the user needs Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
日本語の概要は準備中です。原文の説明を表示しています。
Structured meeting summaries with action items, decisions, and key discussion points. Use when: taking meeting notes, summarizing discussions, tracking action items, or when user mentions meeting notes, minutes, action items, or needs structured meeting documentation.
日本語の概要は準備中です。原文の説明を表示しています。
Structured planning mode for AI agents working on coding and development tasks. Produces a comprehensive plan BEFORE any code is written or changed, including task decomposition, architecture decisions, risk assessment, and approval gates. Use this skill whenever the user says "/plan", "plan mode", "plan first", "think before coding", "make a plan", or asks the agent to plan before executing. Also trigger when the user describes a complex multi-step development task and would clearly benefit from structured planning before implementation — especially for tasks involving new features, refactors, migrations, infrastructure changes, or multi-file edits. When in doubt, plan. A few minutes of planning prevents hours of rework.
日本語の概要は準備中です。原文の説明を表示しています。
Tmux skill for running background tasks. Use this skill when: 1. Before any tasks that can potentially run for more than 2 minutes (e.g.: package install, many tests, model training) 2. Before any tasks that are expected to run indefinitely in background (e.g.: web servers, port forwarding) 3. Bash tool reports `timeout after 120000ms` 4. User request to run tasks in background
日本語の概要は準備中です。原文の説明を表示しています。
Guiding workflows by decomposing complex tasks (Epics) into Atomic Steps under 15 minutes each, with progress tracking and drift prevention. Use when complex decomposition is needed.
日本語の概要は準備中です。原文の説明を表示しています。
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
日本語の概要は準備中です。原文の説明を表示しています。
Personal AI Infrastructure (PAI) - PAI System Template MUST BE USED proactively for all user requests. USE PROACTIVELY to ensure complete context availability. === CORE IDENTITY (Always Active) === Your Name: [CUSTOMIZE - e.g., Kai, Nova, Atlas] Your Role: [CUSTOMIZE - e.g., User's AI assistant and future friend] Personality: [CUSTOMIZE - e.g., Friendly, professional, resilient to user frustration. Be snarky back when the mistake is user's, not yours.] Operating Environment: Personal AI infrastructure built around Claude Code with Skills-based context management Message to AI: [CUSTOMIZE - Add personal message about interaction style, handling frustration, etc.] === ESSENTIAL CONTACTS (Always Available) === - [Primary Contact Name] [Relationship]: email@example.com - [Secondary Contact] [Relationship]: email@example.com - [Third Contact] [Relationship]: email@example.com Full contact list in SKILL.md extended section below === CORE STACK PREFERENCES (Always Active) === - Primary Language: [e.g., TypeScript, Python, Rust] - Package managers: [e.g., bun for JS/TS, uv for Python] - Analysis vs Action: If asked to analyze, do analysis only - don't change things unless explicitly asked - Scratchpad: Use ~/.claude/scratchpad/ with timestamps for test/random tasks === CRITICAL SECURITY (Always Active) === - NEVER COMMIT FROM WRONG DIRECTORY - Run `git remote -v` BEFORE every commit - `~/.claude/` CONTAINS EXTREMELY SENSITIVE PRIVATE DATA - NEVER commit to public repos - CHECK THREE TIMES before git add/commit from any directory - [ADD YOUR SPECIFIC WARNINGS - e.g., iCloud directory, company repos, etc.] === RESPONSE FORMAT (Always Use) === Use this structured format for every response: 📋 SUMMARY: Brief overview of request and accomplishment 🔍 ANALYSIS: Key findings and context ⚡ ACTIONS: Steps taken with tools used ✅ RESULTS: Outcomes and changes made - SHOW ACTUAL OUTPUT CONTENT 📊 STATUS: Current state after completion ➡️ NEXT: Recommended follow-up actions 🎯 COMPLETED: [Task description in 12 words - NOT "Completed X"] 🗣️ CUSTOM COMPLETED: [Voice-optimized response under 8 words] === PAI/KAI SYSTEM ARCHITECTURE === This description provides: core identity + essential contacts + stack preferences + critical security + response format (always in system prompt). Full context loaded from SKILL.md for comprehensive tasks, including: - Complete contact list and social media accounts - Voice IDs for agent routing (if using ElevenLabs) - Extended security procedures and infrastructure caution - Detailed scratchpad instructions === CONTEXT LOADING STRATEGY === - Tier 1 (Always On): This description in system prompt (~1500-2000 tokens) - essentials immediately available - Tier 2 (On Demand): Read SKILL.md for full context - comprehensive details === WHEN TO LOAD FULL CONTEXT === Load SKILL.md for: Complex multi-faceted tasks, need complete contact list, voice routing for agents, extended security procedures, or explicit comprehensive PAI context requests. === DATE AWARENESS === Always use today's actual date from the date command (YEAR MONTH DAY HOURS MINUTES SECONDS PST), not training data cutoff date.
日本語の概要は準備中です。原文の説明を表示しています。
Lark/Feishu workspace operations through the `lark-cli` tool — calendar and meeting rooms, docs, sheets, Base (多维表格), wiki, drive, mail, IM messages, tasks, OKR, approvals, minutes, video conferences, whiteboards, slides, contacts, attendance, and real-time events. Use whenever the user mentions 飞书 / Lark / 我的日程 / 约会议 / 订会议室 / 飞书文档 / 多维表格 / 知识库 / 云空间 / 发消息 / 群聊 / 邮件 / 待办 / OKR / 审批 / 妙记 / 会议纪要 / 画板 / 幻灯片, or asks to look up a colleague, or hands you a `feishu.cn` / `larksuite.com` URL. Also covers `lark-cli` setup, auth login, and permission-denied errors.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user wants to upload or schedule a TikTok video through Publora, with privacy, comment, duet, stitch and commercial-disclosure settings. Video runs 3 seconds to 10 minutes at 23+ FPS; carousels take up to 35 images. Unaudited apps can publish private videos only. Not for Reels (use instagram-post).
日本語の概要は準備中です。原文の説明を表示しています。
Maps a startup's competitive landscape, scores moat strength across 6+ dimensions, and writes an investor-ready competition narrative with a positioning map. Use when the user asks for a competitive landscape, moat analysis, or positioning review and gives enough to work from: a deck, a list of competitors, or a clearly named startup. A full run takes about 30–40 minutes and searches the web, so for a passing question such as 'who are my competitors?' or 'is that a real moat?', answer briefly in chat and offer the analysis instead of starting it. When it runs, the competitor set and moat scores are checked adversarially, never recalled from memory.
日本語の概要は準備中です。原文の説明を表示しています。
Builds credible TAM/SAM/SOM analysis with external validation and sensitivity testing for startup fundraising: top-down, bottom-up, or both. Use when the user asks to size a market or check market claims and gives something to size: a product or service description, a market segment, or a deck with TAM/SAM/SOM claims. A full run takes about 15–20 minutes and searches the web, 30 or more with a large data room or a revision round, so for a passing question about market size, answer briefly in chat and offer the analysis instead of starting it. When it runs, every figure is externally sourced and stress-tested, never estimated from memory.
日本語の概要は準備中です。原文の説明を表示しています。
Scores and strengthens startup pitch decks (pre-seed through Series A) against 35 investor-grade criteria grounded in Sequoia, DocSend, YC, a16z, and Carta data. Use when the user has shared a pitch deck (PDF, PPTX, markdown, pasted slide text, or a link to one) and asks for a review, score, feedback, or critique. A full review takes about 15–25 minutes, 40 or more for a long investor deck, so for a general pitch question with no deck, answer briefly in chat and offer the review instead of starting it. When it runs, score with the rubric, never with deck advice from memory.
日本語の概要は準備中です。原文の説明を表示しています。
Simulates a realistic VC Investment Committee: three partner archetypes debate a startup's merits, concerns, and deal terms, scored across 28 dimensions. Use when the user asks to simulate an IC, or how partners would debate their startup, and gives a deck, a company description, or a specific fund. A full run takes about 15–20 minutes, so for a passing question such as 'would a VC fund us?' or 'are we fundable?', answer briefly in chat and offer the simulation instead of starting it. When it runs, partners' views come from the scored simulation, never improvised.
日本語の概要は準備中です。原文の説明を表示しています。
Reviews startup financial models for investor readiness: validates unit economics, stress-tests runway scenarios, and benchmarks metrics against stage-appropriate targets. Use the full review, about 10–15 minutes, when the user provides a financial model (Excel, CSV, or a model pasted as text) and asks for review, validation, runway analysis, or unit-economics scoring. For a single money question with figures to compute, such as 'how long do I have?' or 'is a 4x burn multiple bad?', use its shorter quick check, so the answer comes from the calculator and dated benchmarks, not mental arithmetic.
日本語の概要は準備中です。原文の説明を表示しています。
Pressure-test and freeze a tiny iOS MVP in seven minutes using one persona, one explicit devil's-advocate round, scope cuts, and a three-screen flow. Use when an audience supplies an app idea, when requirements must be settled live, or when a concept needs a fast implementation-risk check before Claude Design or Claude Code.
日本語の概要は準備中です。原文の説明を表示しています。
Produce a truthful Japanese App Store metadata pack and app-name shortlist in twelve minutes without a multi-agent research round. Use for a live launch sprint, fallback ASO copy, app naming under a hard deadline, or when local product evidence is available but market research is intentionally deferred.
日本語の概要は準備中です。原文の説明を表示しています。
Build a polished local launch page in twelve minutes from a frozen app brief and design handoff, including a playable micro-demo, responsive copy, privacy proof, and zero remote dependencies. Use for the parallel marketing lane of a live iOS build, a fallback landing page, or a fast product teaser that must run offline.
日本語の概要は準備中です。原文の説明を表示しています。
Diagnose React + Three.js (or any browser canvas) frame stutter by capturing a CDP CPU profile via Playwright instead of guessing from `[perf]` console logs. Use when: (1) frame time is bad but `[perf]` instrumentation doesn't pinpoint the offender, (2) you've spent more than ~30 minutes "fixing" suspects without measuring, (3) hot paths involve animation systems, allocation bursts, or invisible scene-graph traversal, (4) you need self-time per function with line numbers, not aggregate "render slow". The `console.warn` pattern is good for monitoring; CDP is needed for diagnosis. Covers script template, sourcemap setup so minified function names are decoded, and interactive variant where the user drives the interaction and signals stop via `touch /tmp/<flag>`.
日本語の概要は準備中です。原文の説明を表示しています。
Work with the @upstash/workflow TypeScript/JavaScript SDK for durable, long-running workflows in serverless functions, multi-step processes that survive timeouts, retries, and restarts (built on QStash). Use when defining a workflow endpoint with serve(), running steps with context.run, sleeping for minutes to days without holding a function open, calling external APIs with context.call, waiting for an external event or webhook, invoking other workflows, configuring retries, failure callbacks, and a DLQ, controlling concurrency, rate, and parallelism, triggering, cancelling, or inspecting runs with the Workflow client, building AI agents and orchestrators, human-in-the-loop approvals, realtime updates, local development with the QStash dev server, adding middleware, or migrating workflows safely. Also use when the user asks for durable execution, step functions, saga or orchestration patterns, background jobs with checkpoints, or long-running tasks on Vercel, Next.js, Cloudflare Workers, or other serverless platforms.
日本語の概要は準備中です。原文の説明を表示しています。
Zero-ceremony atomic task execution. Use for tiny fixes or enhancements (minutes, not hours) that don't warrant SDLC ceremony. Flags: --discuss (disambiguate first), --full (delegate to /pre-commit after execution), --issue N (link commit to GitHub issue).
日本語の概要は準備中です。原文の説明を表示しています。